Curt Tigges

Deep Learning Interpretability Researcher

I do LLM interpretability research at the EleutherAI Institute. My research involves a number of areas, including feature representation and circuit discovery, the study of world modeling, and developmental interpretability. I've also done some work with model training and fine-tuning.

Download Resume

Technical Foci

Mechanistic Interpretability

Most of my research focuses on mechanistic interpretability for large language models. I find discovery of the internal patterns, features, and workings of these models quite exciting, and am also very interested in their application for AI risk reduction.

Developmental Interpretability

In addition to other topics in mechanistic interpretability, I have significant research interest in the evolution of circuitry and capabilities over the training process, with a focus on phase transitions and the sensitivity of models to the order of training data.

Synthetic Dataset Generation & Finetuning

I'm proficient at using LLM prompt generation techniques to generate large datasets for various research purposes.

MLOps & Software Engineering

I maintain a focus on best practices for software engineering in my machine learning projects, and have focused on developing a range of skills surrounding model management, training and deployment.